HILDEGARD: Human-in-the-Loop Data Extraction and Graphically Augmented Relation Discovery

This research paper presents HILDEGARD, an application conceived to guide a semi-expert user in the domain of cultural heritage data management toward the creation of a lightweight knowledge graph tailored for supporting Automatic Story Generation (ASG). For this purpose, a subset of CIDOC-CRM classes and properties is preliminarily selected to fit the domain of interest. The input is constituted by one or more seed-heritage objects selected from a knowledge base. In our case study, they are SPARQL-queried from a Linked Open Database for Italian Cultural Heritage. The shortest path algorithm is then run online on all couplets obtained by a combination of the Wikipedia entities from the selected entry-seeds descriptions. The retrieved entities are subsequently linked to their related DBpedia or YAGO-entry in the chosen language, and the relationships among them are automatically retrieved. The proposed tool addresses different knowledge gaps and societal needs simultaneously, such as the lack of solutions tailored for narrative purposes in the cultural heritage domain, that is, to be used in a scenario where objects belonging to the same room must be linked through a narrative, which shall not only be coherent and informative but also engaging and interesting. The prototype, already able to generate the triples required for the following step of the proposed general ASG pipeline, is intended to be graphically enhanced so that the end user may guide the graph expansion interactively. Received: 25 March 2024 | Revised: 9 July 2024 | Accepted: 18 August 2024 Conflicts of Interest The author declares that he has no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available on GitHub at https://github.com/Glottocrisio/HILDEGARD. Author Contribution Statement Cosimo Palma: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review and editing, Visualization, Project administration.